import cv2
import matplotlib.pyplot as plt
import numpy as np

#  Ideal low Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 50

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        if D <= D0:
            H[u,v] = 1
        else:
            H[u,v] = 0

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

#  Gaussian low Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 50

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        if D <= D0:
            H[u,v] = 1
        else:
            H[u,v] = 0

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

# Butterworth low Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 10
n = 1

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        H[u,v] = 1/(1+(D/D0) ** n)

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

# Ideal High Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 50

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        if D <= D0:
            H[u,v] = 1
        else:
            H[u,v] = 0

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

Hhighpass = 1 - H
plt.imshow(Hhighpass, cmap="gray")
plt.title("Hhighpass")
plt.axis("off")
plt.show()

Gshift = Fshift * Hhighpass
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("Gshift")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("G")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Sharpening ILPF")
plt.axis("off")
plt.show()

#  Gaussian High Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 10

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        H[u,v] = np.exp(-D**2 / (2*D0*D0))

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

Hhighpass = 1 - H
plt.imshow(Hhighpass, cmap="gray")
plt.title("Hhighpass")
plt.axis("off")
plt.show()

Gshift = Fshift * Hhighpass
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("Gshift")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("G")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Sharpening ILPF")
plt.axis("off")
plt.show()

#  Butterworth High Pass Filter
f = cv2.imread(r"C:\Users\Dell\OneDrive\Documents\Chirag\MCA\SEM2\IP\IP Programs\Images\CLogo.png",0)

plt.imshow(f, cmap="gray")
plt.title("f(x,y)")
plt.axis("off")
plt.show()

F = np.fft.fft2(f)
plt.imshow(np.log1p(np.abs(F)), cmap="gray")
plt.title("F")
plt.axis("off")
plt.show()

Fshift = np.fft.fftshift(F)
plt.imshow(np.log1p(np.abs(Fshift)), cmap="gray")
plt.title("F(U,V)")
plt.axis("off")
plt.show()

M,N = f.shape
H = np.zeros((M,N), dtype=np.float32)
D0 = 10
n = 1

for u in range(M):
    for v in range(N):
        D = np.sqrt((u-M/2) ** 2 + (v-N/2) ** 2)
        H[u,v] = 1/(1+(D/D0) ** n)

plt.imshow(H, cmap="gray")
plt.title("H")
plt.axis("off")
plt.show()

Gshift = Fshift * H
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("G(U,V) = F(U,V) * H(U,V)")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("Ginverse(U,V)")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Smoothing ILPF")
plt.axis("off")
plt.show()

Hhighpass = 1 - H
plt.imshow(Hhighpass, cmap="gray")
plt.title("Hhighpass")
plt.axis("off")
plt.show()

Gshift = Fshift * Hhighpass
plt.imshow(np.log1p(np.abs(Gshift)), cmap="gray")
plt.title("Gshift")
plt.axis("off")
plt.show()

G = np.fft.ifftshift(Gshift)
plt.imshow(np.log1p(np.abs(G)), cmap="gray")
plt.title("G")
plt.axis("off")
plt.show()

g = np.abs(np.fft.ifft2(G))
plt.imshow(g, cmap="gray")
plt.title("g(x,y) = Image Sharpening ILPF")
plt.axis("off")
plt.show()